DeepSeek just made agentic coding cheaper on two fronts in one weekend
A cheap open model plus cheap search is a complete agent stack for a small team, and at that point the harness and the tools decide outcomes more than the model does.
DeepSeek released V4.1-Flash-1017 on Friday, and its Terminal-Bench 4.0 score jumps from 31.2 to 42.3. On its own table it beats Kimi K3, GLM 5.3, and GPT-5.6 Sol on most rows, with Opus 5 still ahead overall. The weights are MIT licensed and the context window is 1M. DeepSeek also launched Search and Fetch APIs for agents at $0.75 per 1,000 successful requests, so you only pay for results. If you call them from inside Claude Code, Codex, or DeepSeek Harness, they’re free until November 1, Beijing time.
Sources: huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017 and api-docs.deepseek.com/guides/search
My read: a cheap open model plus cheap search is a complete agent stack for a small team, and at that point the harness and the tools decide outcomes more than the model does.
Your pick: run 1017 on one real coding-agent task this week, and use the free Search and Fetch window in Claude Code or Codex before November 1.
12 months: open models take most agentic coding volume on cost.
24 months: search and fetch become metered utilities inside agent stacks.
36 months: model choice matters less than tool economics.
Why I may be wrong: these are DeepSeek’s own benchmarks, and Opus 5 still leads the hardest rows.
So: is cheap now good enough for your work?